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Record W2038264780 · doi:10.1121/1.4778969

Analysis of monostatic and bistatic reverberation measurements on the Scotian Shelf

2002· article· en· W2038264780 on OpenAlexaffabout
Dale D. Ellis, John R. Preston

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsBathymetryReverberationGeologySonarRange (aeronautics)AcousticsBistatic radarSeabedScatteringOceanographyMarine engineeringRemote sensingComputer scienceOpticsPhysicsMaterials scienceTelecommunicationsRadarEngineering

Abstract

fetched live from OpenAlex

During the Boundary 2001 sea trial, a number of long-range reverberation measurements were made at a site on the Scotian Shelf between Halifax and Sable Island. The water depth was about 80 m over a sandy bottom. The sources were SUS charges dropped from either the NATO research vessel Alliance or the Canadian research vessel CFAV Quest. The receiver was the SACLANTCEN 254-m towed array aboard Alliance. The data were analyzed in two array apertures and frequencies from 80 Hz to 1400 Hz. Model-data comparisons were made using the Generic Sonar Model, with bottom parameters being extracted using both a manual procedure and an automated procedure. Direct measures of the scattering and bottom properties were made by other researchers, including Hines, Holland, and Osler. The bottom topography was fairly smooth near the site, but at long ranges there were numerous scattering features. The polar plots of the data, and model-data differences, are compared with the bathymetric features in the area. [Work supported in part by ONR Code 32, Grant No. N00014-97-1-1034.]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.258
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2002
Admission routes2
Has abstractyes

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